diff --git a/README.md b/README.md
index 8b13789..0634d23 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,3 @@
+# Muse LSL
 
+This is a collection of script to use the muse 2016 BLE headset with LSL.
diff --git a/lsl-record.py b/lsl-record.py
index 2ca3c81..0caffbf 100755
--- a/lsl-record.py
+++ b/lsl-record.py
@@ -1,4 +1,4 @@
-"""Test."""
+#!/usr/bin/env python
 import numpy as np
 import pandas as pd
 from time import time, strftime, gmtime
@@ -71,7 +71,6 @@
 res = np.concatenate(res, axis=0)
 timestamps = np.array(timestamps)
 res = np.c_[timestamps, res]
-print res.shape
 data = pd.DataFrame(data=res, columns=['timestamps'] + ch_names)
 
 data['Marker'] = 0
diff --git a/lsl-viewer.py b/lsl-viewer.py
old mode 100644
new mode 100755
index 60c5048..3dded02
--- a/lsl-viewer.py
+++ b/lsl-viewer.py
@@ -1,4 +1,4 @@
-"""Test."""
+#!/usr/bin/env python
 import numpy as np
 import matplotlib.pyplot as plt
 from scipy.signal import butter, filtfilt
@@ -34,7 +34,6 @@
 (options, args) = parser.parse_args()
 
 figsize = np.int16(options.figure.split('x'))
-print figsize
 
 print("looking for an EEG stream...")
 streams = resolve_byprop('type', 'EEG', timeout=2)
@@ -78,7 +77,7 @@
         k += 1
 dur = time() - t_init
 data = np.concatenate(res, axis=0)
-print data.shape
+
 if options.avgref:
     data -= np.atleast_2d(data.mean(1)).T
 ffts = np.abs(np.fft.fft(data[:, 0:], n=128, axis=0))
@@ -98,7 +97,7 @@
 
 lines = []
 impedances = np.log(ffts[ix_noise].mean(0)) / np.log(ffts[ix_signal].mean(0))
-print impedances
+
 for i, ix in enumerate(picks):
     line, = axes.plot(time[::subsample],
                       data[::subsample, ix] - (i * options.scale * 2),
diff --git a/muse_lsl.py b/muse-lsl.py
similarity index 100%
rename from muse_lsl.py
rename to muse-lsl.py
diff --git a/muse_record.py b/muse-record.py
similarity index 100%
rename from muse_record.py
rename to muse-record.py